Typically, in computed tomography (CT) imaging systems, a rotatable gantry includes an x-ray tube, detector, data acquisition system (DAS), and other components that rotate about a patient table that is positioned at the approximate rotational center of the gantry. X-rays emit from the x-ray tube, are attenuated by the patient, and are received at the detector. The detector typically includes a photodiode-scintillator array of pixelated elements that convert the attenuated x-rays into visible light photons within the scintillator, and then to electrical signals within the photodiode. The electrical signals are digitized and then received and processed within the DAS. The processed signals are transmitted via a slipring (from the rotational side to the stationary side) to a computer for image reconstruction, where an image is formed.
The gantry typically includes a pre-patient collimator that defines or shapes the x-ray beam emitted from the x-ray tube. X-rays passing through the patient can cause x-ray scatter to occur, which can cause image artifacts. Thus, x-ray detectors typically include an anti-scatter grid (ASG) for collimating x-rays received at the detector.
Third generation multi-slices CT scanners typically include detectors having scintillator/photodiodes arrays. These detectors are positioned in an arc where the focal spot is the center of the corresponding circle. These detectors generally have scintillation crystal/photodiode arrays, where the scintillation crystal absorbs x-rays and converts the absorbed energy into visible light. A photodiode is used to convert the light to an electric current. The reading is typically linear to the total energy absorbed in the scintillator.
However, image quality in a CT scanner is dependent on several components in the system such as the detector, the x-ray tube and high voltage generator, the system and component geometry, and the thermal management, etc. In third generation CT scanners, the detector for example, typically has very strict specifications to ensure good image quality and some of these requirements include but are not limited to: a) stability of the detector over time and temperature, b) focal spot drift, c) stable and high light output over the lifetime of the detector, etc.
Typically, CT systems obtain raw data and then reconstruct images using various known pre-processing and post-processing steps to generate a final reconstructed image. That is, CT systems may be calibrated to account for x-ray source spectral properties, detector response, and other features. Raw x-ray data are pre-processed using known steps that include offset correction, reference normalization, and air calibration steps, as examples. Once pre-processed, projection data is obtained by using “minus logarithm” step, which is based on 1) the pre-processed x-ray data which has been attenuated by material through which the x-rays pass, and 2) unattenuated x-rays taking into account some pre-processing steps. The projections may be accumulated, in one example, into a sinogram that is formed by stacking the projections of different views.
Tomographic reconstruction typically occurs using the sinogram to generate an image. The image itself is typically post-processed to reduce various image artifacts.
For instance, one known example of post-processing includes a correction for beam hardening, which is caused from a disproportionate reduction of low-energy photon energies when polychromatic radiation passes through matter. That is, polychromatic x-rays passing through matter tend to have their lower energies attenuated, resulting in a higher energy average spectrum as it passes through an object. The effect is more pronounced for higher attenuating materials, and for portions of the object that are thicker. The effect of beam hardening may be reduced by using a beam filter such as aluminum, copper, or brass, as examples. However, typically such a filter does not meet all clinical requirements and additional software corrections are needed. In one example, beam-hardening is compensated by remapping the projection samples based on known water attenuation characteristics, given the similarity in attenuation characteristics of muscle and water.
Image artifacts may also be caused by other known factors such as aliasing of data, x-ray scatter, detector uniformity, off-focal radiation, detector response characteristics, patient motion, and metal artifacts, as examples. As such, known systems may perform a number of steps for pre- and/or post-processing of data, to account for a variety of known effects, which may be implemented to improve reconstructed CT images.
However, in recent years, larger Z-coverage CT scanners have been introduced, such as 64 slices or beyond. For x-rays emanating from a source such as a focal spot on an x-ray tube, x-ray intensity can vary as a function of detector row angle extending along a z-direction of a CT system. That is, due to the geometry of the anode, x-rays intensity and average energy of the x-ray beam varies as function of the viewing angle with respect to the detector row (in other words, x-rays are generated from certain depth of the tungsten material, and when there emitted, they undergo a certain absorption from the material itself. The amount of absorption depends on the thickness of tungsten material). This difference is called “heel effect” and can negatively affect image quality in CT images due at least to a non-uniformity metric in a Z or body-axis direction.
Thus, there is a need to improve quality in CT systems having a large Z coverage, in systems prone to having a heel effect.